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import pandas as pd
import pdb
import re
import os
data_dir = "/home/share/CorpCDOs/data/swaptions/GS swaptions"
all_df = {}
fwd_index = []
for index in ["IG", "HY"]:
full_path = os.path.join(data_dir, index + " swaptions")
for f in os.listdir(os.path.join(data_dir, index + " swaptions")):
with open(os.path.join(full_path, f), "rb") as fh:
flag = False
masterdf = {}
for line in fh:
line = line.decode('utf-8', 'ignore')
line = line.rstrip()
m = re.search("(IG|HY)(\d{2}) 5y SWAPTION (?:♦GRANULAR♦ )?(?:UPDATE|CLOSES) - Ref\D+(.+)$", line)
if m:
indextype = m.groups()[0]
series = int(m.groups()[1])
if indextype == 'HY':
refprice, refspread = map(float,
re.match("([\S]+)\s+\(([^)]+)\)", m.groups()[2]).groups())
else:
refspread = float(m.groups()[2])
continue
if line.startswith("At"):
quotedate = pd.to_datetime(line[4:])
continue
if line.startswith("Expiry"):
m = re.match("Expiry (\d{2}\w{3}\d{2}) \((?:([\S]+) )?([\S]+)\)", line)
if m:
date, fwprice, fwspread = m.groups()
date = pd.to_datetime(date, format='%d%b%y')
continue
if line.startswith("Stk"):
flag = True
r = []
continue
if flag:
if line:
vals = re.sub(" +", " ", line).split(" ")
if indextype=='HY':
vals.pop(2)
vals.pop(9)
else:
vals.pop(1)
vals.pop(8)
r.append(vals)
continue
else:
if indextype=='HY':
cols = ['Strike', 'Sprd', 'Pay', 'DeltaPay', 'Rec', 'Vol',
'VolChg', 'VolBpd', 'Tail']
else:
cols = ['Strike', 'Pay', 'DeltaPay', 'Rec', 'Vol',
'VolChg', 'VolBpd', 'Tail']
df = pd.DataFrame.from_records(r, columns = cols)
df[['PayBid', 'PayOffer']] = df.Pay.str.split('/', expand=True)
df[['RecBid', 'RecOffer']] = df.Rec.str.split('/', expand=True)
df.drop(['Pay', 'Rec'], axis=1, inplace=True)
for col in df:
df[col] = pd.to_numeric(df[col], errors = 'coerce')
df.set_index('Strike', inplace=True)
d = {'quotedate': quotedate,
'expiry': date,
'index': indextype,
'series': series,
'ref': refspread if indextype =="IG" else refprice}
if indextype == "IG":
d['fwdspread'] = float(fwspread)
else:
d['fwdprice'] = float(fwprice)
fwd_index.append(d)
masterdf[date] = df
flag = False
r = []
continue
all_df[(quotedate, indextype, series)] = pd.concat(masterdf, names=['expiry'])
all_df = pd.concat(all_df, names = ['quotedate', 'index', 'series'])
all_df['DeltaPay'] = - all_df['DeltaPay']/100
all_df['Vol'] /= 100
index_df = pd.DataFrame(fwd_index)
all_df.reset_index(inplace=True)
all_df = all_df.rename(columns={'Strike':'strike',
'Vol': 'vol',
'PayOffer': 'pay_offer',
'PayBid': 'pay_bid',
'RecOffer': 'rec_offer',
'RecBid': 'rec_bid',
'Tail': 'tail',
'DeltaPay': 'delta_pay'})
del all_df['VolBpd'], all_df['VolChg']
if 'Sprd' in all_df:
del all_df['Sprd']
all_df['quote_source'] = 'GS'
index_df = index_df.drop_duplicates(['quotedate', 'index', 'series', 'expiry'])
##insert quotes
from db import dbengine
serenitasdb = dbengine('serenitasdb')
conn = serenitasdb.raw_connection()
## first delete quotes
with conn.cursor() as c:
c.execute("DELETE FROM swaption_quotes WHERE quote_source='GS'")
conn.commit()
all_df.to_sql('swaption_quotes', serenitasdb, if_exists='append', index=False)
sqlstr = "INSERT INTO swaption_ref_quotes(quotedate, index, series, expiry, ref, fwdprice, fwdspread) "\
"VALUES(%(quotedate)s, %(index)s, %(series)s, %(expiry)s, %(ref)s, %(fwdprice)s, %(fwdspread)s) " \
"ON CONFLICT DO NOTHING"
with conn.cursor() as c:
c.executemany(sqlstr, index_df.to_dict(orient='records'))
conn.commit()
conn.close()
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